This thesis addresses three major issues in data mining regarding feature subset selection in large dimensionality domains, plausible reconstruction of incomplete data in cross-sectional applications, and forecasting univariate time series. For the automated selection of an optimal subset of...

This thesis is comprised of three chapters. The first chapter develops a statistical model that enriches the role that firms playin wage determination, allowing firms to influence both average wages as well as the returns to observable worker characteristics. I exploit the hierarchical nature of...

The main purposes of this study were to systematically investigate the impact of representativeness and non-representativeness of common-item sets in terms of statistical, content, and format specifications in mixed-format tests using concurrent calibration with unidimensional IRT models, as...

Measuring continuous change or growth in individual students' academic abilities over time currently uses several statistical models or transformations to move from data representing a student's correct or incorrect responses on individual test items to inferences about the form and quantity of...

If data exhibit a dimensional structure more complex than what is assumed, key conditional independence assumptions of the hypothesized model do not hold. The current work pursues posterior predictive model checking, a flexible family of Bayesian model checking procedures, as a tool for...

The primary purpose of this study is to investigate the impact of the local item dependence (LID) of testlet items on the performance of the multistage tests (MST) that make pass/fail decisions. In this study, LID is simulated in testlet items. Testlet items are those that physically share the...

Recently, researchers have reformulated Item Response Theory (IRT) models into multilevel models to evaluate clustered data appropriately. Using a multilevel model to obtain item difficulty and person ability parameter estimates that correspond directly with IRT models’ parameters is often...

Item Response Theory (IRT) models are the basis of modern educational measurement. In order to increase testing efficiency, modern tests make ample use of groups of questions associated with a single stimulus (testlets). This violates the IRT assumption of local independence. However, a set of...